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Optimization problem

Source: R/optimization_problem.R
optimization_problem.Rd

Create a new optimization problem.

Usage

optimization_problem(x = NULL)

Arguments

x

A NULL or list object. If x is a NULL, then an empty optimization problem is created. Alternately, if a x is a list then a fully formulated optimization problem is created. See Details for more information on the list format. Defaults to NULL.

Value

An OptimizationProblem object.

Details

The argument to x can be a NULL or a list object. If x is a list, then it must have the following elements.

modelsense

character model sense.

number_of_features

integer number of features in problem.

number_of_planning_units

integer number of planning units.

A_i

integer row indices for constraint matrix.

A_j

integer column indices for constraint matrix.

A_x

numeric values for constraint matrix.

obj

numeric objective function values.

lb

numeric lower bound for decision values.

ub

numeric upper bound for decision values.

rhs

numeric right-hand side values.

sense

numeric constraint senses.

vtype

character variable types. These are used to specify that the decision variables are binary ("B"), continuous ("C"), or semi-continuous ("S").

row_ids

character identifiers for the rows in the constraint matrix.

col_ids

character identifiers for the columns in the constraint matrix.

Examples

# create new empty object
x1 <- optimization_problem()

# print new empty object
print(x1)
#> An optimization problem (<OptimizationProblem>)
#> • model sense: missing
#> • dimensions:  0, 0, 0 (rows, columns, cells)
#> • variables:   none

# create list with optimization problem
l <- list(
  modelsense = "min",
  number_of_features = 2,
  number_of_planning_units = 3,
  number_of_zones = 1,
  A_i = c(0L, 1L, 0L, 1L, 0L, 1L),
  A_j = c(0L, 0L, 1L, 1L, 2L, 2L),
  A_x = c(2, 10, 1, 10, 1, 10),
  obj = c(1, 2, 2),
  lb = c(0, 1, 0),
  ub = c(0, 1, 1),
  rhs = c(2, 10),
  compressed_formulation = TRUE,
  sense = c(">=", ">="),
  vtype = c("B", "B", "B"),
  row_ids = c("spp_target", "spp_target"),
  col_ids = c("pu", "pu", "pu")
)

# create fully formulated object based on lists
x2 <- optimization_problem(l)

# print fully formulated object
print(x2)
#> An optimization problem (<OptimizationProblem>)
#> • model sense: min
#> • dimensions:  2, 3, 6 (rows, columns, cells)
#> • variables:   3 (B)